...

random.negativeBinomial

random.negativeBinomial(mu: number, d: number) 🡒 number, pure function

Returns a deviate sampled from a negative binomial distribution of mean mu and of variance $σ^2 = d * μ$ where d is the dispersion. The mean must be non-negative. The dispersion must be greater or equal to 1.

table T = with
  [| as Mu, as Dispersion |]
  [| 0.0,  1.0 |]
  [| 1.5,  1.1 |]
  [| 5.5,  2.0 |]
  [| 10.0, 3.0 |]

show table "" a1c4 with
  T.Mu
  T.Dispersion
  random.negativeBinomial(T.Mu, T.Dispersion)

When the dispersion equals 1, the function random.negativeBinomial is the same as random.poisson.

random.negativeBinomial(mu: number, d: number, zeroInflation: number) 🡒 number, pure function

Overload of the random.negativeBinomial, that returns a deviate sampled from a negative binomial distribution inflated in zero. This probability distribution is the mixture between a dirac in 0 (with a weight equal to the zeroInflation) and the negative binomial of mean mu and of dispersion d (with a weight equal to $1-zeroInflation$). zeroInflation should be in the range $[0, 1]$.

table T = with
  [| as Mu, as Dispersion, as ZeroInflation |]
  [| 0.0,  1.0, 0.1 |]
  [| 1.5,  1.1, 0.2 |]
  [| 5.5,  2.0, 0.3 |]
  [| 10.0, 3.0, 0.4 |]

show table "" a1c4 with
  T.Mu
  T.Dispersion
  T.ZeroInflation
  random.negativeBinomial(T.Mu, T.Dispersion, T.ZeroInflation)

See also

User Contributed Notes
0 notes + add a note